| stepfun {stepfun} | R Documentation |
Step Functions
Description
Given the vectors (x_1,\ldots, x_n) and
(y_0,y_1,\ldots, y_n) (one value more!),
stepfun(x,y,...) returns an interpolating “step” function,
say fn. I.e., fn(t) = c_i (constant) for
t \in (x_i, x_{i+1}) and
fn(x_i) = y_i for i=1,\ldots,n.
The value of the constant c_i above depends on the
“continuity” parameter f.
For the default, f = 0, fn is a “cadlag” function, i.e.
continuous at right, limit (“the point”) at left.
In general, c_i is interpolated in between the
neighbouring y values,
c_i= (1-f) y_i + f\cdot y_{i+1}.
Therefore, for non-0 values of f, fn may no longer be a proper
step function, since it can be discontinuous from both sides.
Usage
stepfun(x, y, f = 0, ties = "ordered")
is.stepfun(x)
knots(Fn, ...)
## S3 method for class 'stepfun'
print(x, digits= getOption("digits") - 2, ...)
## S3 method for class 'stepfun'
summary(object, ...)
Arguments
x |
numeric vector giving the knots or jump locations of the step
function for |
y |
numeric vector one longer than |
f |
a number between 0 and 1, indicating how interpolation outside
the given x values should happen. See |
ties |
Handling of tied |
Fn, object |
an R object inheriting from |
digits |
number of significant digits to use, see |
... |
potentially further arguments (require by the generic). |
Value
A function of class "stepfun", say fn.
There are methods available for summarizing ("summary(.)"),
representing ("print(.)") and plotting ("plot(.)", see
plot.stepfun) "stepfun" objects.
The environment of fn contains all the
information needed;
"x","y"the original arguments
"n"number of knots (x values)
"f"continuity parameter
"yleft", "yright"the function values outside the knots;
"method"(always
== "constant", fromapproxfun(.)).
The knots are also available by knots(fn).
Author(s)
Martin Maechler, maechler@stat.math.ethz.ch with some basic code from Thomas Lumley.
See Also
ecdf for empirical distribution functions as
special step functions and plot.stepfun for plotting
step functions.
approxfun and splinefun.
Examples
y0 <- c(1,2,4,3)
sfun0 <- stepfun(1:3, y0, f = 0)
sfun.2 <- stepfun(1:3, y0, f = .2)
sfun1 <- stepfun(1:3, y0, f = 1)
sfun0
summary(sfun0)
summary(sfun.2)
x0 <- seq(0.5,3.5, by = 0.25)
rbind(x=x0, f.f0 = sfun0(x0), f.f02= sfun.2(x0), f.f1 = sfun1(x0))